Automatic parameter estimation and detection of Saimaa ringed seal knocking vocalizations

Abstract

ABSTRACTThe Saimaa ringed seal (Pusa hispida saimensis) is an endangered subspecies of ringed seal that inhabits Finland’s Lake Saimaa. Many efforts have been put into studying their ecology; however, these initiatives heavily rely on human intervention, making them costly. This study first analyzes an extensive dataset of acoustic recordings from Lake Saimaa with a focus on “knocking” vocalizations, the most commonly found Saimaa ringed seal call type. Then, the dataset is used to train and test a binary deep learning classification system to detect these vocalizations. Out of the 8996 annotated knocking events, the model is trained and tuned with 8096 samples and tested with the remaining 900 events. The system achieves a 97% F1-Score in the test set, demonstrating its capacity to identify knocking segments from noise and other events.